Computer Assisted Coding: Market Shares, Strategies, and Forecasts, Worldwide, 2016 to 2022

Published: Mar, 2017 | Pages: 299 | Publisher: WinterGreen Research
Industry: ICT | Report Format: Electronic (PDF)

Computer assisted coding of medical information uses natural language solutions to link the physician notes in an electronic patient record to the codes used for billing Medicare, Medicaid, and private insurance companies.

Natural language processing is used determine the links to codes. 88% of the coding can occur automatically without human review. Computer assisted coding is used in all parts of the healthcare delivery system. The coding systems work well to implement automated coding process.

Physicians think about patient conditions in terms of words. Software is configured to achieve working with physicians who are more comfortable describing a patient treatment in words than codes. The electronic patient record, created using physician dictation, is used to form the base for the coding. Natural language solutions implement computer coding to identify key words and patterns of language. The physician dictation can be done using regular language that the software recognizes and translates into billing codes.

Properly designed natural language processing (NLP) solutions do not require physicians to change the way they work. They can dictate in a free-flowing fashion, consistent with the way they think, and are not limited to structured inputs that may or may not fully capture the unique circumstances of each patient encounter.

Matching codes generated from physician notes to standard treatment protocols promises to improve health care delivery. Accompanying that type of physician patient management against best practice promises to revolutionize health care delivery. The ability to further check as to whether the recommendations for follow up made by radiologists and matching the commendations with the actual follow up heralds’ significant promise of vastly improved health care delivery.

Computer assisted coding applications depend on the development of production quality natural language processing (NLP)-based computer assisted coding applications. This requires a process-driven approach to software development and quality assurance.

A well-defined software engineering process consists of requirements analysis, preliminary design, detailed design, implementation, unit testing, system testing and deployment. NLP complex technology defines the key features of a computer assisted coding (CAC) application.

Automation of process will revolutionize health care delivery. In addition to automating the insurance, billing, and transaction systems, streamlined care delivery is an added benefit. The ability to look at workflow and compare actual care to best practice is fundamental to automated business process.

The ability to link diagnostic patient information to treatment regimes and drug prescriptions is central to improving medical care delivery. Once a physician can see what conditions need to be followed, and see that appropriate care has been prescribed 100% of the time, care delivery improves dramatically. Diagnosis of conditions using radiology frequently results in detection of events that need follow-up.

According to Susan Eustis, lead author of the team that prepared the study, “Growing acceptance of computer assisted coding for physician offices represents a shift to cloud computing and billing by the procedure coded. Because SaaS based CAC provides an improvement over current coding techniques the value is being recognized. Administrators are realizing the benefits to quality of care. Patients feel better after robotic surgery and the surgeries are more likely to be successful.”

The worldwide market for Computer Assisted Coding is $2.8 billion in 2016, anticipated to reach $5.1 billion by 2023. The complete report provides a comprehensive analysis of Computer Assisted Coding in different categories, illustrating the diversity of software market segments. A complete procedure analysis is done, looking at numbers of procedures and doing penetration analysis.

Major health plans report a smooth transition to ICD-10. This is due to rigorous testing for six years. ICD-10 has had a positive impact on reimbursement. ICD-10 coding system requires use of 72,000 procedure codes and 68,000 CM codes, as opposed to the 4,000 and 14,000 in the ICD-9 system. Managing high volume of codes requires automation. Healthcare providers and payers use complex coding systems, which drives demand for technologically advanced CAC systems.

The market for computer-assisted coding grows because it provides management of workflow process value by encouraging increasing efficiency in care delivery. By making more granular demarcation of diagnoses and care provided for each diagnosis, greater visibility into the care delivery system is provided. Greater visibility brings more ability to adapt the system to successful treatments.

WinterGreen Research is an independent research organization funded by the sale of market research studies all over the world and by the implementation of ROI models that are used to calculate the total cost of ownership of equipment, services, and software. The company has 35 distributors worldwide, including Global Information Info Shop, Market Research.com, Research and Markets, electronics.ca, and Thompson Financial. It conducts its business with integrity.

The increasingly global nature of science, technology and engineering is a reflection of the implementation of the globally integrated enterprise. Customers trust wintergreen research to work alongside them to ensure the success of the participation in a particular market segment.

WinterGreen Research supports various market segment programs; provides trusted technical services to the marketing departments. It carries out accurate market share and forecast analysis services for a range of commercial and government customers globally. These are all vital market research support solutions requiring trust and integrity.

Key Topics

• Natural Language Coding
• NLC
• Computer Assisted Coding
• CAC
• Rules Based Coding Technology
• Medical Coding
• Medical Necessity
• Electronic Medical Record
• Electronic Medical Coding
• Natural language solutions
• Computerized medical workflow
• Claims scrubbers
• Tessi® (terminology supported semantic indexing)
• Electronic coding for physicians
• Medical necessity
• Correct coding tools
• Physician electronic medical record (emr) systems
• Language and computing
• Ontology assisted solutions
• Diagnosis codes
• Procedure codes

 Table of Content

COMPUTER ASSISTED CODING EXECUTIVE SUMMARY 18
Medical Best Practice Linking 21
CAC for Coders 21
Computer Assisted Coding Best Practice 24
Coding Solutions 26
Physician Computer Assisted Coding Services 28
Natural Language Computer Assisted Coding Market Shares 29
Natural Language Computer Assisted Coding of Medical Procedures Forecasts 31
Medical Best Practice Linking 33

1. COMPUTER ASSISTED CODING MARKET DESCRIPTION AND MARKET DYNAMICS 34
1.1 Coding Challenge 34
1.1.1 Computer Assisted Coding (CAC) 34
1.1.2 Advances In Natural Language Processing And Informatics 36
1.1.3 Using Electronic Health Record (EHR) Documentation To Generate Codes 37
1.2 Computer-Assisted Coding 38
1.2.1 Physician Practice Industry Forces Affecting Development of CAC 39
1.2.2 Application of CAC Technology 41
1.3 Development of a CAC Tool For Hospital Inpatient Use 42
1.3.1 CAC Impact on the Coding Workflow 42
1.3.2 Computers Replace Human Coders 42
1.3.3 CAC Applied Without Human Intervention Depends On Critical Differences Between
CAC Systems 43
1.4 Healthcare Industry Largest In United States 44
1.4.1 Building a Safer Health System 46
1.4.2 Facilitating the Use of Technology in the Healthcare Industry 47
1.4.3 Prescription Drug Modernization 48
1.5 Medical Necessity and Medical Necessity Errors 49
1.6 Physician Office Electronic Coding 50
1.6.1 CAC Automates and Accelerates Auditing 54
1.7 Natural Language Solutions 54
1.7.1 State Of Language Technology Evaluation 55
1.8 Computerized Workflow System 57
1.8.1 Confidence Assessment Module 58
1.8.2 Researching Electronic Coding Products: 60

2. COMPUTER ASSISTED CODING MARKET SHARES AND FORECASTS 61
2.1.1 Medical Best Practice Linking 64
2.1.2 CAC for Coders 64
2.1.3 Computer Assisted Coding Best Practice 67
2.1.4 Coding Solutions 69
2.1.5 Physician Computer Assisted Coding Services 71
2.2 Natural Language Computer Assisted Coding Market Shares 72
2.2.1 3M 75
2.2.2 3M 77
2.2.3 3M Merging Quality With Reimbursement 80
2.2.4 Optum 81
2.2.5 Optum Automated Code Identification 82
2.2.6 Optum 85
2.2.7 nThrive / Precyse 86
2.2.8 Dolbey 86
2.2.9 McKesson 88
2.2.10 Cerner 90
2.2.11 TruCode 90
2.3 Natural Language Computer Assisted Coding of Medical Procedures Forecasts 90
2.3.1 CAC Market Software and Services Segmentation 94
2.3.2 CAC Hospitals and Facilities and Physicians Market Segment 96
2.3.3 Computer Assisted Coding Physician Market 98
2.3.4 Worldwide Computer Assisted Coding, Hospitals and Facilities and Physicians 100
2.3.5 CAC Software Market Hospital and Physician Segments 102
2.3.6 CAC Services Market Segment 103
2.3.7 US Computer Assisted Coding Physician Software License / Maintenance and Cloud
SaaS Services 104
2.3.8 Physicians Computer Assisted Coding 107
2.3.9 US Computer Assisted Coding Software Units 110
2.3.10 US Computer Assisted Coding Software / Cloud Services for Independent Radiology
Clinics Market Forecasts 112
2.3.1 US Independent Radiology Imaging Centers 113
2.3.2 Erroneous Selection of Principal Diagnoses Impacting Reimbursement 114
2.3.3 Growth of the U.S. Healthcare Industry 118
2.4 Worldwide, Number of Patients and Procedures 120
2.5 Making The Shift To The Modern ICD-10 Requirements 124
2.6 Computer Assisted Coding Prices 125
2.7 Computer Assisted Coding Regional Analysis 126
2.7.1 3M 360 Encompass System 129

3. COMPUTER ASSISTED CODING PRODUCT DESCRIPTION 130
3.1 3M 130
3.1.1 3M 360 Encompass System 131
3.1.2 3M 3M CodeAssist System 133
3.1.3 3M APR DRG Solutions Aspects 139
3.1.4 3M Merging Quality With Reimbursement 140
3.1.5 3M APR DRG Software 142
3.1.6 3 M Classification System For Patients 142
3.1.7 3M APR DRG Software Features: 145
3.1.8 3M Coding Technology 147
3.1.9 3M Computer-Assisted Coding Solutions 148
3.1.10 3M Medical Coding Tools Streamline Processes 148
3.1.11 CodeAssist Automating the Medical Coding Process 149
3.1.12 3M CodeComplete Outsource Solution for Medical Coding 150
3.1.13 3M DataScout Clinical Data Extraction and Identification 150
3.1.14 3M and American Academy of Professional Coders (AAPC) 152
3.1.15 3M Data Mining Technology 153
3.1.16 3M Systems for Overcoming Documentation Shortfalls 154
3.1.17 3M Solutions for a Changing Healthcare Landscape 158
3.1.18 3M Web-Based Coding Software Return on Investment 171
3.1.19 3M Coding Software Functions 173
3.1.20 3M Computer-Assisted Coding Solutions Targeted to Specialty Areas 175
3.1.21 3M CodeAssist Functions 176
3.1.22 3M CodeComplete Business Process Management 177
3.2 Dolbey 179
3.2.1 Dolbey Coding Productivity Management 181
3.2.2 Dolby Fusion Suite Modules 183
3.3 Optum Coding Service 187
3.3.1 Optum Coding 188
3.3.2 Optum CPT Codes 189
3.3.3 Optum Medicare Fee Schedule 189
3.4 McKesson 191
3.4.1 Mckesson Watching the Cash 192
3.4.2 McKesson Securing the Subsidy 193
3.4.3 McKesson Quality Control And Process Improvement 195
3.5 Cerner Computer Assisted Coding 196
3.6 Platocode Computer-Assisted Coding 199
3.6.1 Platocode ICD 10 202
3.6.2 Platocode Solution For Ambulatory Surgery 202
3.6.3 Platocode API 203
3.6.4 Communication Between 3rd-Party Applications And A Platocode Server 203
3.7 Nuance Computer Assisted Coding 203
3.7.1 Nuance Clinical Documentation Review 204
3.7.2 Nuance Clinical Documentation Compliance 205
3.7.3 Nuance Clintegrity Computer Assited Coding (CAC) 205
3.7.4 Nuance Clintegrity Computer Assisted Coding (CAC) Key Features 208
3.7.5 Nuance Clintegrity Facility Coding Solutions for Healthcare 208
3.7.6 Nuance Clintegrity Facility Coding 210
3.7.7 Nuance Clintegrity Computer Assisted Coding (CAC) Features 211
3.7.8 Nuance Clintegrity Physician Coding 212
3.7.9 Nuance Clinician Reimbursement Calculation 214
3.7.10 Nuance Clintegrity Compliance & ICD-10 Transition 215
3.7.11 Nuance Clintegrity Facility Coding 216
3.7.12 Nuance Clintegrity Abstracting 216
3.7.13 Nuance Clintegrity ICD-10 Education Services 218
3.7.14 Nuance Automated Coding 221
3.7.15 Nuance Natural Language Processing 222
3.7.16 Nuance Natural Language Understanding 222
3.7.17 Nuance Mapping and Modeling Disparate Controlled Medical Vocabularies (CMVs); 223
3.8 Artificial Medical Intelligence Emscribe CAC 223
3.8.1 Artificial Medical Intelligence EMscribe Dynamic Search 225
3.8.2 Artificial Medical Intelligence EMscribe Encoder 226
3.8.3 AMI EMscribe Dynamic Medical Term And Coding Search Tool 227
3.8.4 Artificial Medical Intelligence Autonomous Coding 228
3.8.5 Artificial Medical Intelligence (AMI) EMscribe Dx 229
3.9 CodeCorrect 232
3.9.1 CodeCorrect Capture Revenue and Maintain Compliance 232
3.9.2 CodeCorrect knowledge 232
3.9.3 CodeCorrect Medical Necessity Verification and APC Performance Tools 233
3.9.4 QuadraMed 234
3.10 M*Modal Coding 234
3.10.1 M*Modal Workflow 236
3.10.2 M*Modal Management Tools 236
3.10.3 M*Modal Single Platform 236
3.11 nThrive / MedAssets-Precyse and Equation 237
3.11.1 Precyse Medical Coding and Computer Assisted Coding 237

4. COMPUTER ASSISTED CODING RESEARCH AND TECHNOLOGY 240
4.1 Computer-Assisted Coding Technology 240
4.2 Hybrid Technology 244
4.2.1 Computer Assisted Coding Engine 244
4.3 Optum Computer Assisted Coding Technology 246
4.4 Preventable Medical Conditions 247
4.5 Natural Language Processing (NLP) Medical Coding 248
4.5.1 Rules Based Approaches 248
4.5.2 Reports Based On Statistics 248
4.5.3 Normalize the Data 249
4.6 Reports Must Be In Some Kind Of Electronic Format 249
4.6.1 NLP Software Statistical Analysis 250
4.6.2 Workflow 250
4.6.3 Feedback for Machine Learning 250
4.6.4 Coding 251
4.6.5 Accuracy And Specificity Of Retrieval 252
4.6.6 Natural Language Programming (NLP) Vocabulary Processor 252
4.6.7 Robust Underlying Terminological Model And A Component Architecture 253
4.7 TeSSI (Terminology Supported Semantic Indexing) 254
4.7.1 L&C’s LinkBase Medical Ontology 254
4.7.2 Semantic Indexing With The TeSSI Indexing Engine 255
4.7.3 Semantic Indexing Solution Automates The Indexing Process 256
4.7.4 Information Extraction with TeSSI Extraction Engine 259
4.7.5 Semantic Search with TeSSI Search Engine 260

5. COMPUTER ASSISTED CODING COMPANY PROFILES 261
5.1 CAC Key Market Players 261
5.2 3M 262
5.2.1 3M Business 263
5.2.2 3M Health Care Segment 266
5.2.3 3M Electronics and Energy Business 267
5.2.4 3M Health Information Systems 267
5.3 Artificial Medical Intelligence 271
5.4 Cerner 271
5.4.1 Cerner Business 272
5.4.2 Cerner Acquired Siemens Health Services 273
5.4.3 Cerner 2016 Fourth Quarter and Full-Year Highlights: 273
5.5 Craneware 273
5.6 Dolbey 274
5.7 EPIC 274
5.8 Group One / CodeCorrect 275
5.9 M*Modal 276
5.10 nThrive 277
5.10.1 nThrive / Precyse 277
5.11 Nuance 278
5.11.1 Nuance Healthcare 279
5.11.2 Nuance Business Description 279
5.11.3 Nuance Key Metrics 280
5.11.4 Nuance Healthcare Trends 281
5.12 Quest Diagnostics 282
5.13 TruCode283
5.14 UnitedHealth Group / Optum 284
5.14.1 UnitedHealth Group / Optum 285
5.14.2 UnitedHealth Group Optum Health Information Technology Acquires Clinical Data Analytics Vendor Humedica285
5.14.3 Optum Acquires Physician Practice Management And Revenue Management Software Firm, MedSynergies and Support Arm of
ProHealth Physicians Group 286
5.14.4 Optum MedSynergies Synergies 289
5.14.5 Optum Life Sciences 291
5.14.6 United Healthcare Revenue 292
5.15 Selected CAC Companies 294

List of Figures

Figure 1. Computer Assisted Coding of Medical Information Market Driving Forces 19
Figure 2. Computer Assisted Coding of Medical Information Market Driving Factors 20
Figure 3. CAC Workstation Coder Benefits 22
Figure 4. CAC Management Tools 23
Figure 5. ELECTRONIC CODING SOLUTION MARKET DRIVING FORCES 27
Figure 6. ELECTRONIC CODING PRODUCT ISSUES 28
Figure 7. Computer Assisted Coding Software and Services Market Shares, Dollars, 2016 30
Figure 8. Computer Assisted Coding Market Forecast, Dollars, Worldwide, 2017-2024 32
Figure 9. Barriers to CAC 41
Figure 10. Electronic Coding Integrated Database Issues 51
Figure 11. Medical Necessity Online 52
Figure 12. Physician Office Computer Assisted Coding Key Benefits: 53
Figure 13. Natural Language Solutions System For Coding 55
Figure 14. Computerized Workflow System Systems Features 57
Figure 15. 3M Confidence Assessment Module System 59
Figure 16. Computer Assisted Coding of Medical Information Market Driving Forces 62
Figure 17. Computer Assisted Coding of Medical Information Market Driving Factors 63
Figure 18. CAC Workstation Coder Benefits 65
Figure 19. CAC Management Tools 66
Figure 20. ELECTRONIC CODING SOLUTION MARKET DRIVING FORCES 70
Figure 21. ELECTRONIC CODING PRODUCT ISSUES 71
Figure 22. Computer Assisted Coding Software and Services Market Shares, Dollars, 2016 73
Figure 23. Worldwide Computer Assisted Coding License Shipments and Cloud Services
Market Shares, Dollars, 2016 74
Figure 24. 3M CAC Research Areas 76
Figure 25. 3M Core of NLP Computer Assisted Coding 78
Figure 26. Optum CAC Key Benefits: 82
Figure 27. Optum LifeCode, CAC Functions 83
Figure 28. Optum LifeCode, CAC Reconciliation Functions 84
Figure 29. Optum CAC Reconciliation Module Functions: 85
Figure 30. Platocode Computer Assisted Coding Solution Benefits 88
Figure 31. Computer Assisted Coding Market Forecast, Dollars, Worldwide, 2017-2024 92
Figure 32. Computer Assisted Coding CAC Market Forecasts, Dollars, 2017 to 2023 93
Figure 33. CAC Market Segments Software and Services Key Topics 95
Figure 34. Worldwide Computer Assisted Coding Hospitals and Facilities and Physicians
Market Shares, Dollars, 2016 96
Figure 35. Worldwide Computer Assisted Coding: Large Teaching Hospitals, Mid-Size and
Small Hospitals, and Clinical Facilities, Market Shares, Units, 2016 97
Figure 36. Worldwide Computer Assisted Coding, Hospitals and Facilities and Physicians,
Market Shares, Units, 2016 100
Figure 37. Worldwide Computer Assisted Coding, License Shipments, Services, and Cloud
Services 101
Figure 38. Worldwide and US Computer Assisted Coding Number of Large Physician Practices,
CAC Installed Base, Market Forecasts, Number, 2017-2023 104
Figure 39. Worldwide and US Computer Assisted Coding Software and Cloud Services
CAC Market Forecasts, Dollars, 2017-2023 105
Figure 40. Worldwide and US Computer Assisted Coding for Physicians CAC Market
Forecasts, Dollars, 2017-2023 107
Figure 41. US Computer Assisted Coding Physician Software License / Maintenance and
Cloud SaaS Services, CAC Market Forecasts, Dollars, 2017-2023 108
Figure 42. US Computer Assisted Coding Software License / Maintenance and Cloud SaaS
Services CAC For Large Independent Physician Practices Market Forecasts, Dollars, 2017-2023 109
Figure 43. US Computer Assisted Coding Software Units Retired CAC For Large
Independent Physician Practices Market Forecasts, 2017-2023 110
Figure 44. US Computer Assisted Coding Software Units Retired CAC For Large
Independent Physician Practices Market Forecasts, 2017-2023 111
Figure 45. US Computer Assisted Coding Software and Cloud SaaS Services CAC For
Independent Radiology Clinics Market Forecasts, Dollars, 2017-2023 112
Figure 46. US Computer Assisted Coding CAC Software License / Maintenance and
Cloud SaaS Percent Penetration For Independent Radiology Clinics Market Forecasts,
Dollars, 2017-2023 113
Figure 47. US Outpatient Procedures Forecasts, Number of Procedures, 2016-2023 120
Figure 48. US Computer Assisted Coding Outpatient Procedure Market Penetration
Forecasts, % Penetration, 2017-2023 121
Figure 49. 3M APR DRG Software Functions: 123
2.5 Making The Shift To The Modern ICD-10 Requirements 124
Figure 50. Computer Assisted Coding Regional Market Segments Dollars, Worldwide, 2016 127
Figure 51. Computer Assisted Coding Regional Market Segments Dollars, Worldwide, 2016 128
Figure 52. 3M 360 Encompass 1,500 Hospitals And Healthcare User Organizations 129
Figure 53. 3M 360 Encompass 1,500 Hospitals And Healthcare User Organizations 131
Figure 54. 3M 3M CodeAssist System Features 133
Figure 55. 3M Codefinder Functions 135
Figure 56. 3M Codefinder Features 136
Figure 57. 3M Codefinder Intelligent Functions 138
Figure 58. 3M APR DRG Solutions Aspects 139
Figure 59. 3M Applications For Severity- And Risk-Adjusted Data 141
Figure 60. 3M Classification System 144
Figure 61. 3M APR DRG Software Features 145
Figure 62. 3M Medical Coding Tools 149
Figure 63. 3M DataScout Functions 151
Figure 64. 3M Clinical Information Extraction Functions 152
Figure 65. 3M Systems For Overcoming Documentation Shortfalls Focus 155
Figure 66. 3M Systems Topics 156
Figure 67. 3M Systems Metrics Included For Computerized Coding 157
Figure 68. 3M Web-Based Coding Software Return On Investment Metrics 171
Figure 69. 3M Web-Based Coding Software Key Benefits 172
Figure 70. 3M Coding Software Functions 173
Figure 71. 3M Coding Software Features 173
Figure 72. 3M Internet-Based Computer-Assisted Medical Coding Target Markets 175
Figure 73. 3M CodeAssist Functions 177
Figure 74. 3M CodeComplete Functions 178
Figure 75. Dolbey Fusion CAC Benefits 180
Figure 76. Dolbey Computer-Assisted Coding Solution Features 182
Figure 77. Dolby Computer Assisted Coding CAC Fusion Suite Modules 185
Figure 78. Optum Computer-Assisted Coding (CAC) Intelligent CAC Functions: 187
Figure 79. Optum Coding Service 188
Figure 80. Optum Medicare Fee Schedule 190
Figure 81. McKesson Practice Management Priorities 192
Figure 82. Cerner Discern nCode Functions 197
Figure 83. Cerner Discern nCode Key Features 198
Figure 84. Platocode Process 200
Figure 85. PlatoCode Code Set Filters 201
Figure 86. Nuance Personnel Impacted by Transition to ICD-10 206
Figure 87. ICD-10 Critical Business Concerns: 207
Figure 88. Nuance Clintegrity Facility Coding Healthcare Solutions Platform Functions 209
Figure 89. Nuance Clintegrity Facility Coding Healthcare Solution Functions 210
Figure 90. Nuance Clintegrity Computer Assisted Coding (CAC) Professional Fee Coding Functions 213
Figure 91. Nuance Clintegrity Clinician Coding Features 214
Figure 92. Nuance Clintegrity Facility Coding Features 216
Figure 93. Nuance Clintegrity Platform Modules 217
Figure 94. Nuance Clintegrity Platform, Modules Customizable Data Collection Fields Features218
Figure 95. Nuance Advantages Of Automating Coding With Clintegrity 220
Figure 96. Nuance Coding Algorithms 221
Figure 97. Nuance Mapping And Modeling Disparate Controlled Medical Vocabulary Functions223
Figure 98. Artificial Medical Intelligence EMscribe CAC 224
Figure 99. Artificial Medical Intelligence EMscribe Dynamic Search 225
Figure 100. Artificial Medical Intelligence (Ami) Emscribe Dx Benefits 231
Figure 101. Precyse Coding Services 238
Figure 102. PrecyseCode CAC Coding Functions 239
Figure 103. Computer Assisted Technology Functions 241
Figure 104. How ICD-9 and ICD-10 Are Different 245
Figure 105. ICD-9 and ICD-10 Different Formats 246
Figure 106. Semantic Indexing for Medical Ontology 257
Figure 107. Semantic Process Flow Index Component Medical Ontology 258
Figure 108. Information Extraction With Tessi Extraction Engine Functions 259
Figure 109. 3M 360 Encompass 1,500 Hospitals And Healthcare User Organizations 270
Figure 110. Current EPIC Computer Assisted Coding CAC Integrations 274